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http://dx.doi.org/10.5762/KAIS.2019.20.2.26

Harmony Search for Virtual Machine Replacement  

Choi, Jae-Ho (Defence Agency for Technology and Quality)
Kim, Jang-Yeop (Kwang Woon University)
Seo, Young Jin (Defence Agency for Technology and Quality)
Kim, Young-Hyun (Defence Agency for Technology and Quality)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.20, no.2, 2019 , pp. 26-35 More about this Journal
Abstract
By operating servers, storage, and networking devices, Data centers consume a lot of power such as cooling facilities, air conditioning facilities, and emergency power facilities. In the United States, The power consumed by data centers accounted for 1.8% of total power consumption in 2004. The data center industry has evolved to a large scale, and the number of large hyper scale data centers is expected to grow in the future. However, as a result of examining the server share of the data center, There is a problem where the server is not used effectively such that the average occupancy rate is only about 15% to 20%. To solve this problem, we propose a Virtual Machine Reallocation research using virtual machine migration function. In this paper, we use meta-heuristic for effective virtual machine reallocation. The virtual machine reallocation problem with the goal of maximizing the idle server was designed and solved through experiments. This study aims to reducing the idle rate of data center servers and reducing power consumption simultaneously by solving problems.
Keywords
Meta Heuristic; Migration; Harmony Search; Visualization; Virtual Machine Reallocation;
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  • Reference
1 J. H. Bang, "The data center is 'Electric Eating Hippo' & When you are on the Internet,", The Hankyoreh, 2015.06.
2 Y. J. Bae, "Korea is a data center battleground & Reasons for global companies coming in one after another", Chosun NewsPress, 2017.10.
3 M. J. KIM, "Gangwon-do Data Center Status and Future Tasks", The Bank of Korea, 2018.04.
4 Data Center Knowledge, "Research: There are Now Close to 400 Hyper-Scale Data Centers in the World", 2017.12.
5 W.Vogels, "Beyond Server Consolidation", ACM Queue, 2008.01.-02.
6 S. Crosby, and D.Brown, "Virtualization reality", ACM Queue, 2006.12.
7 P. Timalsena, "A Study of The impact of Virtualization on Computer Networks", Master's thesis, 2013.
8 Redhat, "Virtualization Deployment and Administration Guide"
9 S.-H. Wang, P. P.-W. Huang, C. H.-P. Wen, and L.-C. Wang, "Eqvmp: Energy-efficient and qos-aware virtual machine placement for software defined datacenter networks," in Information Networking (ICOIN), 2014 International Conference on. IEEE, pp. 220-225, 2014.
10 T. Ferreto, C. A. De Rose, and H.-U. Heiss, "Maximum migration time guarantees in dynamic server consolidation for virtualized data centers," in Euro-Par 2011 Parallel Processing. Springer, pp. 443-454, 2011.
11 D. Dong and J. Herbert, "Energy efficient vm placement supported by data analytic service," in Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on. IEEE, pp. 648-655, 2013
12 X. Zhang, Q. Yue, and Z. He, "Dynamic energy-efficient virtual machine placement optimization for virtualized clouds," in Proceedings of the 2013 International Conference on Electrical and Information Technologies for Rail Transportation (EITRT2013)-Volume II. Springer, pp. 439-448, 2014.
13 W. Shi and B. Hong, "Towards profitable virtual machine placement in the data center," in Utility and Cloud Computing (UCC), 2011 Fourth IEEE International Conference on. IEEE, pp. 138-145, 2011.
14 I. Hwang and M. Pedram, "Hierarchical virtual machine consolidation in a cloud computing system," in Cloud Computing (CLOUD), 2013 IEEE Sixth International Conference on. IEEE, pp. 196-203, 2013.
15 Y. Gao, H. Guan, Z. Qi, Y. Hou, and L. Liu, "A multi-objective ant colony system algorithm for virtual machine placement in cloud computing," Journal of Computer and System Sciences, vol. 79, no. 8, pp. 1230-1242, 2013.   DOI
16 H. Jin, D. Pan, J. Xu, and N. Pissinou, "Efficient vm placement with multiple deterministic and stochastic resources in data centers," in Global Communications Conference (GLOBECOM), 2012 IEEE. IEEE, pp. 2505-2510, 2012.
17 W. Li, J. Tordsson, and E. Elmroth, "Virtual machine placement for predictable and time-constrained peak loads," in Economics of Grids, Clouds, Systems, and Services. Springer, pp. 120-134. 2012.
18 Eli M. Dow, "Decomposed multi-objective bin-packing for virtual machine consolidation", PeerJ Computer Science, 2016.
19 O. Biran, A. Corradi, M. Fanelli, L. Foschini, A. Nus, D. Raz, and E. Silvera, "A stable network-aware vm placement for cloud systems," in Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012). IEEE Computer Society, pp. 498-506, 2012.
20 W. Wang, H. Chen, and X. Chen, "An availability-aware virtual machine placement approach for dynamic scaling of cloud applications," Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on. IEEE, pp. 509-516, 2012.
21 J. Xu and J. A. Fortes, "Multi-objective virtual machine placement in virtualized data center environments," in Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom). IEEE, pp. 179-188, 2010.
22 C. C. T. Mark, D. Niyato, and T. Chen-Khong, "Evolutionary optimal virtual machine placement and demand forecaster for cloud computing," in Advanced Information Networking and Applications (AINA), 2011 IEEE International Conference on. IEEE, pp. 348-355, 2011.
23 A. C. Adamuthe, R. M. Pandharpatte, and G. T. Thampi, "Multiobjective virtual machine placement in cloud environment," in Cloud & Ubiquitous Computing & Emerging Technologies (CUBE), 2013 International Conference on. IEEE, pp. 8-13, 2013.
24 G. Wu, M. Tang, Y.-C. Tian, and W. Li, "Energy-efficient virtual machine placement in data centers by genetic algorithm," in Neural Information Processing. Springer, pp. 315-323, 2012.
25 A. Murtazaev, SY. Oh, "Sercon: Server Consolidation Algorithm using Live Migration of Virtual Machines for Green Computing", IETE Technical Review, 28:3, 212-231, 2014.   DOI
26 Y. Wu, M. Tang, and W. Fraser, "A simulated annealing algorithm for energy efficient virtual machine placement," in Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on. IEEE, pp. 1245-1250, 2012.
27 T. Ferreto, C. A. De Rose, and H.-U. Heiss, "Maximum migration time guarantees in dynamic server consolidation for virtualized data centers," in Euro-Par 2011 Parallel Processing. Springer, pp. 443-454, 2011.